This study aimed to project the current and future suitable habitats of three primary malaria vectors in China—An. lesteri, An. minimus, and An. sinensis—using an ensemble modeling approach. We simulated their geographical distributions under current and future climates (SSP126, SSP245, SSP585) using the Biomod2 platform with 19 bioclimatic variables and elevation. The ensemble models achieved high predictive performance, as reflected by AUC and TSS values. Environmental drivers were species-specific: An. lesteri was primarily influenced by elevation, temperature seasonality (Bio4), and seasonal precipitation (Bio18, Bio19); An. minimus by the mean temperature of the coldest quarter (Bio11); and An. sinensis by annual precipitation (Bio12), mean temperature of the wettest quarter (Bio8), and elevation. Future projections revealed divergent responses: the habitat of An. lesteri is projected to contract and shift northeastward; An. sinensis is expected to expand northward, potentially extending climatically suitable areas into new regions; and although the overall range of An. minimus remains stable, its internal suitability shifts toward higher classes under warming. These findings demonstrate that climate change will critically reshape the distribution of major malaria vectors across China, underscoring the need to integrate climate-informed projections into adaptive surveillance and vector control strategies in the post-elimination era.
Jiang et al. (Thu,) studied this question.
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